Magnetic impurity in the vicinity of a vacancy in bilayer graphene

We use quantum Monte Carlo method to study a magnetic impurity located next to a vacancy in bilayer graphene with Bernal stacking. Due to the broken symmetry between two sublattices in bilayer system, there exist two different types of vacancy induced localized state. We find that the magnetic property of the adatom located on the adjacent site of the vacancy depends on whether the vacancy belongs to A or B sublattice. In general, local moment is more strongly suppressed if the vacancy belongs to the sublattice A when $\mu \sim 0$. We switch the values of the chemical potential and study the basic thermodynamic quantities and the correlation functions between the magnetic adatom and the carbon sites.Comment: 3 pages, 4 figures, conferenc

A novel approach for the assessment of morphological evolution based on observed water levels in tide-dominated estuaries

Assessing the impacts of both natural (e.g., tidal forcing from the ocean) and human-induced changes (e.g., dredging for navigation, land reclamation) on estuarine morphology is particularly important for the protection and management of the estuarine environment. In this study, a novel analytical approach is proposed for the assessment of estuarine morphological evolution in terms of tidally averaged depth on the basis of the observed water levels along the estuary. The key lies in deriving a relationship between wave celerity and tidal damping or amplification. For given observed water levels at two gauging stations, it is possible to have a first estimation of both wave celerity (distance divided by tidal travelling time) and tidal damping or amplification rate (tidal range difference divided by distance), which can then be used to predict the morphological changes via an inverse analytical model for tidal hydrodynamics. The proposed method is applied to the Lingdingyang Bay of the Pearl River Estuary, located on the southern coast of China, to analyse the historical development of the tidal hydrodynamics and morphological evolution. The analytical results show surprisingly good correspondence with observed water depth and volume in this system. The merit of the proposed method is that it provides a simple approach for understanding the decadal evolution of the estuarine morphology through the use of observed water levels, which are usually available and can be easily measured.National Key R&D of China (Grant No. 2016YFC0402601), National Natural Science Foundation of China (Grant No. 51979296, 51709287, 41706088, 41476073), Fundamental Research Funds for the Central Universities (No.18lgpy29) and from the Water Resource Science and Technology Innovation Program of Guangdong Province (Grant No. 2016-20, 2016-21). The work of the second author was supported by FCT research contracts IF/00661/2014/CP1234.info:eu-repo/semantics/submittedVersio

Smart Content Recognition from Images Using a Mixture of Convolutional Neural Networks

With rapid development of the Internet, web contents become huge. Most of the websites are publicly available, and anyone can access the contents from anywhere such as workplace, home and even schools. Nevertheless, not all the web contents are appropriate for all users, especially children. An example of these contents is pornography images which should be restricted to certain age group. Besides, these images are not safe for work (NSFW) in which employees should not be seen accessing such contents during work. Recently, convolutional neural networks have been successfully applied to many computer vision problems. Inspired by these successes, we propose a mixture of convolutional neural networks for adult content recognition. Unlike other works, our method is formulated on a weighted sum of multiple deep neural network models. The weights of each CNN models are expressed as a linear regression problem learned using Ordinary Least Squares (OLS). Experimental results demonstrate that the proposed model outperforms both single CNN model and the average sum of CNN models in adult content recognition.Comment: To be published in LNEE, Code: github.com/mundher/NSF

Surface reconstruction, premelting, and collapse of open-cell nanoporous Cu via thermal annealing

We systematic investigate the collapse of a set of open-cell nanoporous Cu (np-Cu) with the same porosity and shapes, but different specific surface area, during thermal annealing, via performing large-scale molecular dynamics simulations. Surface premelting is dominated in their collapses, and surface premelting temperatures reduce linearly with the increase of specific surface area. The collapse mechanisms are different for np-Cu with different specific surface area. If the specific surface area less than a critical value ($\sim$ 2.38 nm$^{-1}$), direct surface premelting, giving rise to the transition of ligaments from solid to liquid states, is the cause to facilitate falling-down of np-Cu during thermal annealing. While surface premelting and following recrystallization, accelerating the sloughing of ligaments and annihilation of pores, is the other mechanism, as exceeding the critical specific surface area. The recrystallization occurs at the temperatures below supercooling, where liquid is instable and instantaneous. Thermal-induced surface reconstruction prompts surface premelting via facilitating local "disordering" and "chaotic" at the surface, which are the preferred sites for surface premelting

Emergence of intrinsic superconductivity below 1.178 K in the topologically non-trivial semimetal state of CaSn3

Topological materials which are also superconducting are of great current interest, since they may exhibit a non-trivial topologically-mediated superconducting phase. Although there have been many reports of pressure-tuned or chemical-doping-induced superconductivity in a variety of topological materials, there have been few examples of intrinsic, ambient pressure superconductivity in a topological system having a stoichiometric composition. Here, we report that the pure intermetallic CaSn3 not only exhibits topological fermion properties but also has a superconducting phase at 1.178 K under ambient pressure. The topological fermion properties, including the nearly zero quasi-particle mass and the non-trivial Berry phase accumulated in cyclotron motions, were revealed from the de Haas-van Alphen (dHvA) quantum oscillation studies of this material. Although CaSn3 was previously reported to be superconducting at 4.2K, our studies show that the superconductivity at 4.2K is extrinsic and caused by Sn on the degraded surface, whereas its intrinsic bulk superconducting transition occurs at 1.178 K. These findings make CaSn3 a promising candidate for exploring new exotic states arising from the interplay between non-trivial band topology and superconductivity, e.g. topological superconductivityComment: 20 pages,4 figure